library(openxlsx)
# allC = merge(p1C,p2C,by.x="Sample",by.y="Sample")
popsOfInterestFile="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/finalCounts/popsOfInterest.txt"
popsOfInterest=read.delim(popsOfInterestFile, stringsAsFactors = FALSE, sep = "\t")
popsOfInterest$POPCOMP=gsub(" ",".",popsOfInterest$POPCOMP)
popsOfInterest$POPF=gsub(" ",".",popsOfInterest$POPF)
popsOfInterest$POPHRS1000=gsub(" ",".",popsOfInterest$POPHRS1000)
popsOfInterest$POPM=gsub(" ",".",popsOfInterest$POPM)
# popsOfInterest$POPM=gsub(")",".",popsOfInterest$POPM,fixed = TRUE)
# popsOfInterest$POPM=gsub("(",".",popsOfInterest$POPM,fixed = TRUE)
popsOfInterest$POPJ=gsub(" ",".",popsOfInterest$POPJ)
popsOfInterest$POPJ=gsub(")",".",popsOfInterest$POPJ,fixed = TRUE)
popsOfInterest$POPJ=gsub("(",".",popsOfInterest$POPJ,fixed = TRUE)
releasedFile="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/FULL/releasedSamples.txt"
released = read.delim(releasedFile,
header = TRUE,
stringsAsFactors = FALSE)
noBadsFile="/Users/Kitty/git/auto-fcs/explore/openCyto/extractManualComp/manualUse.txt"
noBads = read.delim(noBadsFile,
header = TRUE,
stringsAsFactors = FALSE)
dir="/Volumes/Beta/data/flow/results_r25_25full_SS_SubCD8_SCD14_Manuals/finalCountsFreqCBC/"
p1="p1.cnts.frqs.cbcs.xlsx"
p2="all.p2.xlsx"
p2Test=read.xlsx(paste0(dir,p2), sheet=2)
for(thing in colnames(p2Test)){
print(paste0(thing, " ",max(as.numeric(p2Test[,c(thing)]),na.rm = TRUE) ))
}
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): NAs introduced by coercion
## Warning in max(as.numeric(p2Test[, c(thing)]), na.rm = TRUE): no non-
## missing arguments to max; returning -Inf
## [1] "Sample -Inf"
## [1] "Manual;0=Regular,1=Manual,2=DCSub,3=ocFail 3"
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): NAs introduced by coercion
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): no non-missing arguments to max; returning -Inf
## [1] "F_ID -Inf"
## [1] "DATE 43024"
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): NAs introduced by coercion
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): no non-missing arguments to max; returning -Inf
## [1] "MACHINE -Inf"
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): NAs introduced by coercion
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): no non-missing arguments to max; returning -Inf
## [1] "EXPERIMENTER -Inf"
## Warning in paste0(thing, " ", max(as.numeric(p2Test[, c(thing)]), na.rm =
## TRUE)): NAs introduced by coercion
## [1] "Live.Single.PBMCs 1090134"
## [1] "DC.NK.MONOCYTES 0.970588235294118"
## [1] "DC.NK 0.846153846153846"
## [1] "MONOCYTES 0.870967741935484"
## [1] "Classical.monocytes 356.666666666667"
## [1] "Non.classical.monocytes 3.03827751196172"
## [1] "NK 0.487232957105566"
## [1] "NK.CD56HI 0.419505404520144"
## [1] "NK.CD56LO.Fixed 1"
## [1] "DC 0.846153846153846"
## [1] "Plasmacytoid.DC 1"
## [1] "Myeloid.DC 1"
addCols=c("Sample", "Manual", "MACHINE", "F_ID", "DATE", "EXPERIMENTER")
sheets = list(c("COUNTS",1),c("FREQ",2),c("CBCS",3))
parse <- function(dir,p,sheet,extractPop,addCols,manualRms) {
pd= read.xlsx(paste0(dir,p), sheet=as.numeric(sheet[2]))
colnames(pd) =gsub("Manual.*","Manual",colnames(pd))
colnames(pd) =gsub(".Fixed","",colnames(pd),fixed = TRUE)
extract = c(addCols,extractPop[!is.na(extractPop)])
have=( extract %in% colnames(pd))
print(table(have))
print(extract[have])
pE = pd[,extract[have]]
pE$METRIC=sheet[1]
#
use = (pE$F_ID %in% manualRms$Study.ID)
pE$RELEASED=use
return(pE)
}
p1All=data.frame()
p2All=data.frame()
p1Filt = read.xlsx(paste0(dir,p1), sheet=1)
namesP1=p1Filt[which(p1Filt$`Live.cells.(PE-)`>20000),]$Sample
p2Filt = read.xlsx(paste0(dir,p2), sheet=1)
namesP2=p2Filt[which(p2Filt$`Live.Single.PBMCs`>20000),]$Sample
for(sheet in sheets){
p1d=parse(dir=dir,p=p1,sheet=sheet,extractPop =popsOfInterest$POPM,addCols = addCols,manualRms=released )
usep1=p1d$Sample %in% namesP1
p1d=p1d[usep1,]
p1All=rbind(p1All,p1d)
p2d=parse(dir=dir,p=p2,sheet=sheet,extractPop =popsOfInterest$POPCOMP,addCols = addCols,manualRms=released )
usep2=p2d$Sample %in% namesP2
p2d=p2d[usep2,]
#
# usep2=p2d$Sample %in% noBads$x
# p2d=p2d[usep2,]
print(colnames(p2d))
print(colnames(p2All))
p2All=rbind(p2All,p2d)
}
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [19] "RELEASED"
## character(0)
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [19] "RELEASED"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [19] "RELEASED"
## have
## FALSE TRUE
## 11 13
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "naive.Bcells.(CD27-.IgD+)" "cytotoxic.Tcells-CD8+"
## [9] "Tcells.(CD3+.CD19-)" "IgD-.memory.Bcells.(CD27+)"
## [11] "IgD+.memory.Bcells.(CD27+)" "Helper.Tcells-CD4+"
## [13] "B.cells.(CD3-.CD19+)"
## have
## FALSE TRUE
## 9 17
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [19] "RELEASED"
## [1] "Sample" "Manual"
## [3] "MACHINE" "F_ID"
## [5] "DATE" "EXPERIMENTER"
## [7] "Non.classical.monocytes" "Myeloid.DC"
## [9] "DC.NK" "MONOCYTES"
## [11] "NK" "DC.NK.MONOCYTES"
## [13] "NK.CD56HI" "NK.CD56LO"
## [15] "Plasmacytoid.DC" "Classical.monocytes"
## [17] "DC" "METRIC"
## [19] "RELEASED"
p1All$DATE=as.Date(p1All$DATE,origin='1899-12-30')
## Warning in strptime(xx, f <- "%Y-%m-%d", tz = "GMT"): unknown timezone
## 'zone/tz/2017c.1.0/zoneinfo/America/Chicago'
p2All$DATE=as.Date(p2All$DATE, origin = '1899-12-30')
p2All$Manual=gsub("2","0",p2All$Manua)
p2All$Manual=gsub("1","0",p2All$Manua)
p2All$Manual=gsub("3","0",p2All$Manua)
# p2All[which(p2All$DC>60000&p2All$METRIC=="COUNTS"),]$F_ID
# p2All$DATE_MONTH <- as.Date(cut(as.Date(p2All$DATE),
# breaks = "month"))
# pAll$DATE_MONTH <- as.Date(cut(as.Date(pAll$DATE),
# breaks = "month"))
popsOfInterest$PANEL1= popsOfInterest$POPM %in% colnames(p1All)
popsOfInterest$PANEL2= popsOfInterest$POPCOMP %in% colnames(p2All)
p1JflowCounts= read.delim("/Volumes/Beta/data/flow/compManual/p1.cnts.xln", stringsAsFactors = FALSE)
p1JflowCounts$Sample=p1JflowCounts$FILE
p2JflowCounts= read.delim("/Volumes/Beta/data/flow/compManual/p2.cnts.xln", stringsAsFactors = FALSE)
p2JflowCounts$Sample=p2JflowCounts$FILE
origPercents =read.xlsx("/Volumes/Beta/data/flow/HRS1000 REPORT.xlsx", sheet=1)
origCBCs =read.xlsx("/Volumes/Beta/data/flow/HRS1000 REPORT.xlsx", sheet=3)
origPercentP2 =read.xlsx("/Volumes/Beta/data/flow/p2.newGateTree.xlsx", sheet=2)
origPercentP2$Sample=gsub(".*/","",origPercentP2$X1)
library(ggplot2)
t2 <- theme(
axis.line = element_line(colour = "black"),
axis.text = element_text(colour = "black"),
axis.ticks = element_line(colour = "black"),
# panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
# panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
# legend.position="none",
axis.text.x=element_text(angle=90,hjust=1)
)
theme_set(theme_grey(base_size = 18))
summarize <- function(oc,manual,mergeOCCol,mergeManCol,ocCol,manualCol) {
merge=merge(oc,manual,by.x=mergeOCCol,by.y=mergeManCol)
print(table(merge$Manual))
numManuals=length(merge[which(merge$Manual=="1"),][,ocCol])
merge=merge[which(merge$Manual=="0"&merge$RELEASED),]
t1 =cor.test(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)]),method = "pearson",na.action="na.omit")
t2=cor.test(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)]),method = "spearman",na.action="na.omit")
medianOCFreq=median(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
meanOCFreq=mean(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
sdOCFreq=sd(as.numeric(merge[,c(ocCol)]),na.rm = TRUE)
# print(plot(as.numeric(merge[,c(ocCol)]),as.numeric(merge[,c(manualCol)])))
medianManualFreq=median(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
meanManualFreq=mean(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
sdManualFreq=sd(as.numeric(merge[,c(manualCol)]),na.rm = TRUE)
g= ggplot(merge,aes(x=as.numeric(merge[,c(ocCol)]),y=as.numeric(merge[,c(manualCol)]))) +
geom_point() +
xlab(paste0("OC ",ocCol)) +
ylab(paste0("Manual ",ocCol))+ggtitle(paste0("pearson = ",t1$estimate, "\n spearman = ", t2$estimate, "\nn=", length(merge[,c(ocCol)]) ))
print(g)
tmp = data.frame(
OC_POP = ocCol,
ManualPop = manualCol,
N = length(merge[,c(ocCol)]),
PEARSON = t1$estimate,
SPEARMAN = t2$estimate,
MEDIAN_OC = medianOCFreq,
MEDIAN_MANUAL = medianManualFreq,
ABS_DIFF_MEDIAN = abs(medianOCFreq-medianManualFreq),
MEAN_OC = meanOCFreq,
MEAN_MANUAL = meanManualFreq,
ABS_DIFF_MEAN = abs(meanOCFreq-meanManualFreq),
SD_OC = sdOCFreq,
SD_MANUAL = sdManualFreq,
ABS_DIFF_SD = abs(sdOCFreq-sdManualFreq),
NUM_MANUALS_REMOVED=numManuals
)
return(tmp)
}
forMerge=c("Sample","DATE" , "MACHINE" , "EXPERIMENTER")
stats <- function(data,machine=TRUE) {
require(MASS)
formula <- TARGET ~ DATE + MACHINE + EXPERIMENTER
if(!machine){
formula <- TARGET ~ DATE + EXPERIMENTER
}
fit <- lm(formula, data = data)
step <- stepAIC(fit, direction = "both")
t=summary(step)
ps=as.data.frame(t$coefficients)
f=summary(eval(t$call))
result=paste0("MODEL=",t$call[2],";MODEL_ADJ_R_SQUARED=",f$adj.r.squared," ;pvals=",paste0(ps$`Pr(>|t|)`[2:length(ps$`Pr(>|t|)`)],collapse = ","))
return(result)
# print(step$anova)
}
results=data.frame()
for(pop in popsOfInterest$POPM){
if(!is.na(pop)){
for(metric in sheets){
jflow=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPJ
origColumn=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPHRS1000
compLook=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPM
if(popsOfInterest[which(popsOfInterest$POPM==pop),]$PANEL1){
print(paste0(pop," panel1 ",metric[1]))
if(metric[1]=="COUNTS"){
tmp =summarize(p1All[which(p1All$METRIC==metric[1]),],p1JflowCounts,"Sample","Sample",pop,jflow)
tmp$METRIC=metric[1]
tmp$PANEL="panel1"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=NA
tmp$COMP_LOOK=compLook
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=NA
tmp$CONFOUNDING_MODEL_OC_MANUAL_MATCHED=NA
tmp$CONFOUNDING_MODEL_MANUAL=NA
results=rbind(results,tmp)
} else if(metric[1]=="FREQ"){
useOrigPercents =origPercents[which(origPercents[,c(origColumn)]<1000),]
tmp =summarize(p1All[which(p1All$METRIC==metric[1]),],useOrigPercents,"F_ID","Study.ID",pop,origColumn)
tmp$METRIC=metric[1]
tmp$PANEL="panel1"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=length(origPercents[,c(origColumn)])-length(useOrigPercents[,c(origColumn)])
tmp$COMP_LOOK=compLook
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=NA
tmp$CONFOUNDING_MODEL_OC_MANUAL_MATCHED=NA
tmp$CONFOUNDING_MODEL_MANUAL=NA
results=rbind(results,tmp)
}
}else if(popsOfInterest[which(popsOfInterest$POPM==pop),]$PANEL2){
print(paste0(pop," panel2 ",metric[1]))
if(metric[1]=="COUNTS"){
tmp =summarize(p2All[which(p2All$METRIC==metric[1]),],p2JflowCounts,"Sample","Sample",popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP,jflow)
tmp$METRIC=metric[1]
tmp$PANEL="panel2"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=NA
tmp$COMP_LOOK=compLook
subData=p2All[which(p2All$METRIC==metric[1]),]
subData$TARGET=as.numeric(subData[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=NA
r= stats(subData)
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=r
tmp$CONFOUNDING_MODEL_OC_MANUAL_MATCHED=NA
tmp$CONFOUNDING_MODEL_MANUAL=NA
results=rbind(results,tmp)
} else if(metric[1]=="FREQ"){
ocColumnTmp=popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP
useOrigPercents =origPercentP2[which(origPercentP2[,c(ocColumnTmp)]<1000),]
origTmp=ocColumnTmp
if(ocColumnTmp==origTmp){
ocColumnTmp=paste0(ocColumnTmp,".x")
origTmp=paste0(origTmp,".y")
}
tmp =summarize(p2All[which(p2All$METRIC==metric[1]),],origPercentP2,"Sample","Sample",ocColumnTmp,origTmp)
tmp$METRIC=metric[1]
tmp$PANEL="panel2"
tmp$NUM_MANUAL_POPS_ZEROED_OUT=length(origPercentP2[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])-length(useOrigPercents[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])
tmp$COMP_LOOK=compLook
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=NA
subDataP2=p2All[which(p2All$METRIC==metric[1]&p2All$Manual=="0"),]
subDataP2$TARGET=as.numeric(subDataP2[,c(popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)])
r= stats(subDataP2)
tmp$CONFOUNDING_MODEL_OC_ALL_SAMPLES=r
forMergeHere =c(forMerge,popsOfInterest[which(popsOfInterest$POPM==pop),]$POPCOMP)
subData=origPercentP2
subData =merge(subDataP2[,forMergeHere],subData,by.x = "Sample",by.y = "Sample")
subData$TARGET=as.numeric(subData[,ocColumnTmp])
r= stats(subData,machine = FALSE)
tmp$CONFOUNDING_MODEL_OC_MANUAL_MATCHED=r
subData$TARGET=as.numeric(subData[,origTmp])
tmp$CONFOUNDING_MODEL_MANUAL =NA
r= stats(subData,machine = FALSE)
tmp$CONFOUNDING_MODEL_MANUAL=r
results=rbind(results,tmp)
}
}
}
}
}
## [1] "naive.Bcells.(CD27-.IgD+) panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "naive.Bcells.(CD27-.IgD+) panel1 FREQ"
##
## 0 1
## 924 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "naive.Bcells.(CD27-.IgD+) panel1 CBCS"
## [1] "cytotoxic.Tcells-CD8+ panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "cytotoxic.Tcells-CD8+ panel1 FREQ"
##
## 0 1
## 924 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "cytotoxic.Tcells-CD8+ panel1 CBCS"
## [1] "Tcells.(CD3+.CD19-) panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Tcells.(CD3+.CD19-) panel1 FREQ"
##
## 0 1
## 924 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Tcells.(CD3+.CD19-) panel1 CBCS"
## [1] "IgD-.memory.Bcells.(CD27+) panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD-.memory.Bcells.(CD27+) panel1 FREQ"
##
## 0 1
## 853 19
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD-.memory.Bcells.(CD27+) panel1 CBCS"
## [1] "IgD+.memory.Bcells.(CD27+) panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD+.memory.Bcells.(CD27+) panel1 FREQ"
##
## 0 1
## 853 19
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "IgD+.memory.Bcells.(CD27+) panel1 CBCS"
## [1] "Helper.Tcells-CD4+ panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Helper.Tcells-CD4+ panel1 FREQ"
##
## 0 1
## 924 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "Helper.Tcells-CD4+ panel1 CBCS"
## [1] "B.cells.(CD3-.CD19+) panel1 COUNTS"
##
## 0 1
## 928 31
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "B.cells.(CD3-.CD19+) panel1 FREQ"
##
## 0 1
## 924 33
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## [1] "B.cells.(CD3-.CD19+) panel1 CBCS"
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Loading required package: MASS
## Start: AIC=134694.9
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 2.9754e+10 134695
## - MACHINE 1 10852172 2.9765e+10 134696
## - DATE 1 52630422 2.9807e+10 134709
## - EXPERIMENTER 4 176981548 2.9931e+10 134740
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-51149.65
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.004079 29.657 -51150
## <none> 29.652 -51150
## - EXPERIMENTER 4 0.083478 29.736 -51132
## - DATE 1 0.068881 29.721 -51131
##
## Step: AIC=-51150.42
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 29.657 -51150
## + MACHINE 1 0.004079 29.652 -51150
## - EXPERIMENTER 4 0.091445 29.748 -51131
## - DATE 1 0.083453 29.740 -51127
## Start: AIC=-4723.79
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.001232 3.6977 -4725.5
## - EXPERIMENTER 2 0.012850 3.7093 -4724.8
## <none> 3.6965 -4723.8
##
## Step: AIC=-4725.5
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.014639 3.7124 -4726.1
## <none> 3.6977 -4725.5
## + DATE 1 0.001232 3.6965 -4723.8
##
## Step: AIC=-4726.07
## TARGET ~ 1
##
## Df Sum of Sq RSS AIC
## <none> 3.7124 -4726.1
## + EXPERIMENTER 2 0.0146385 3.6977 -4725.5
## + DATE 1 0.0030205 3.7093 -4724.8
## Start: AIC=-5810.62
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 1.0553 -5810.6
## - EXPERIMENTER 2 0.012040 1.0674 -5804.8
## - DATE 1 0.021912 1.0772 -5794.8
## [1] "Non.classical.monocytes.(CD16+.CD14+) panel2 CBCS"
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=148689.4
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 1.4211e+11 148689
## - DATE 1 87951812 1.4220e+11 148693
## - MACHINE 1 173308388 1.4228e+11 148698
## - EXPERIMENTER 4 3599489649 1.4571e+11 148906
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-34957.19
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 180.92 -34957
## - EXPERIMENTER 4 0.86878 181.79 -34922
## - DATE 1 0.90991 181.83 -34914
## - MACHINE 1 1.07497 181.99 -34906
## Start: AIC=-3439.91
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 16.252 -3439.9
## - EXPERIMENTER 2 0.16743 16.419 -3435.0
## - DATE 1 0.15527 16.407 -3433.7
## Start: AIC=-3666.64
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.00150 12.514 -3668.5
## <none> 12.512 -3666.6
## - EXPERIMENTER 2 0.60783 13.120 -3629.5
##
## Step: AIC=-3668.53
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 12.514 -3668.5
## + DATE 1 0.00150 12.512 -3666.6
## - EXPERIMENTER 2 0.69474 13.208 -3625.7
## [1] "Myeloid.DC.(CD11c+.CD123-) panel2 CBCS"
## [1] "DC.NK.(CD20-.CD14-) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=184247.5
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 7.4594e+12 184248
## - MACHINE 1 2.2361e+09 7.4616e+12 184248
## - DATE 1 5.2880e+09 7.4647e+12 184252
## - EXPERIMENTER 4 2.6077e+10 7.4855e+12 184271
## [1] "DC.NK.(CD20-.CD14-) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-47230.99
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.0168559 46.294 -47236
## - MACHINE 1 0.0019917 46.279 -47233
## <none> 46.277 -47231
## - DATE 1 0.0123955 46.289 -47231
##
## Step: AIC=-47235.73
## TARGET ~ DATE + MACHINE
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.0007737 46.294 -47238
## <none> 46.294 -47236
## - DATE 1 0.0307978 46.324 -47232
## + EXPERIMENTER 4 0.0168559 46.277 -47231
##
## Step: AIC=-47237.58
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 46.294 -47238
## + MACHINE 1 0.0007737 46.294 -47236
## - DATE 1 0.0304829 46.325 -47234
## + EXPERIMENTER 4 0.0156380 46.279 -47233
## Start: AIC=-4614.26
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.001388 4.1956 -4618.0
## <none> 4.1942 -4614.3
## - DATE 1 0.057896 4.2521 -4604.4
##
## Step: AIC=-4617.98
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 4.1956 -4618.0
## + EXPERIMENTER 2 0.001388 4.1942 -4614.3
## - DATE 1 0.072686 4.2683 -4605.1
## Start: AIC=-4557.81
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.007876 4.4843 -4560.3
## <none> 4.4764 -4557.8
## - DATE 1 0.066395 4.5428 -4547.0
##
## Step: AIC=-4560.28
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 4.4843 -4560.3
## + EXPERIMENTER 2 0.007876 4.4764 -4557.8
## - DATE 1 0.090763 4.5751 -4544.9
## [1] "DC.NK.(CD20-.CD14-) panel2 CBCS"
## [1] "MONOCYTES.(CD14+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=178706
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 6.3721e+07 4.0132e+12 178704
## <none> 4.0131e+12 178706
## - MACHINE 1 4.6084e+09 4.0178e+12 178714
## - EXPERIMENTER 4 7.7597e+10 4.0907e+12 178870
##
## Step: AIC=178704.1
## TARGET ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 4.0132e+12 178704
## + DATE 1 6.3721e+07 4.0131e+12 178706
## - MACHINE 1 4.6440e+09 4.0179e+12 178712
## - EXPERIMENTER 4 9.6019e+10 4.1092e+12 178908
## [1] "MONOCYTES.(CD14+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-49350.19
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 36.539 -49350
## - DATE 1 0.01125 36.550 -49349
## - MACHINE 1 0.02218 36.561 -49347
## - EXPERIMENTER 4 0.72435 37.264 -49182
## Start: AIC=-4771.41
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 3.4989 -4771.4
## - DATE 1 0.008593 3.5075 -4771.3
## - EXPERIMENTER 2 0.033380 3.5323 -4767.2
## Start: AIC=-4688.79
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.000138 3.8489 -4690.8
## <none> 3.8487 -4688.8
## - EXPERIMENTER 2 0.041272 3.8900 -4683.5
##
## Step: AIC=-4690.76
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 3.8489 -4690.8
## + DATE 1 0.000138 3.8487 -4688.8
## - EXPERIMENTER 2 0.046877 3.8958 -4684.3
## [1] "MONOCYTES.(CD14+) panel2 CBCS"
## [1] "NK.(CD16+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=180588.3
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 4.9501e+12 180588
## - MACHINE 1 4.6892e+09 4.9547e+12 180595
## - DATE 1 6.4042e+09 4.9565e+12 180598
## - EXPERIMENTER 4 1.3858e+10 4.9639e+12 180605
## [1] "NK.(CD16+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-51274.16
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.018659 29.504 -51276
## <none> 29.485 -51274
## - MACHINE 1 0.009999 29.495 -51273
## - DATE 1 0.038992 29.524 -51264
##
## Step: AIC=-51276.48
## TARGET ~ DATE + MACHINE
##
## Df Sum of Sq RSS AIC
## <none> 29.504 -51276
## - MACHINE 1 0.006757 29.511 -51276
## + EXPERIMENTER 4 0.018659 29.485 -51274
## - DATE 1 0.046427 29.551 -51264
## Start: AIC=-4968.92
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.0042791 2.7904 -4971.6
## <none> 2.7861 -4968.9
## - DATE 1 0.0161010 2.8022 -4965.9
##
## Step: AIC=-4971.59
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 2.7904 -4971.6
## - DATE 1 0.0119759 2.8024 -4969.9
## + EXPERIMENTER 2 0.0042791 2.7861 -4968.9
## Start: AIC=-4905.85
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.0070254 3.0034 -4907.8
## <none> 2.9963 -4905.9
## - DATE 1 0.0279020 3.0242 -4899.8
##
## Step: AIC=-4907.82
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 3.0034 -4907.8
## + EXPERIMENTER 2 0.0070254 2.9963 -4905.9
## - DATE 1 0.0210759 3.0244 -4903.8
## [1] "NK.(CD16+) panel2 CBCS"
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=192559.4
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 7.4834e+08 1.8843e+13 192558
## <none> 1.8842e+13 192559
## - MACHINE 1 1.5859e+10 1.8858e+13 192565
## - EXPERIMENTER 4 1.9519e+11 1.9038e+13 192644
##
## Step: AIC=192557.8
## TARGET ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 1.8843e+13 192558
## + DATE 1 7.4834e+08 1.8842e+13 192559
## - MACHINE 1 1.5141e+10 1.8858e+13 192563
## - EXPERIMENTER 4 2.3513e+11 1.9078e+13 192661
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-37724.94
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 133.54 -37725
## - DATE 1 0.10880 133.65 -37720
## - MACHINE 1 0.16737 133.71 -37716
## - EXPERIMENTER 4 1.28795 134.83 -37647
## Start: AIC=-3724.66
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 11.702 -3724.7
## - EXPERIMENTER 2 0.12959 11.832 -3719.1
## - DATE 1 0.15821 11.860 -3715.0
## Start: AIC=-3833.45
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 10.322 -3833.5
## - EXPERIMENTER 2 0.12020 10.442 -3827.4
## - DATE 1 0.11237 10.435 -3826.1
## [1] "DC.NK.MONOCYTES.(CD3-.CD19-) panel2 CBCS"
## [1] "NK.CD56HI panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=108068.8
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 13406 1527145856 108067
## <none> 1527132449 108069
## - DATE 1 724413 1527856863 108071
## - EXPERIMENTER 4 2056441 1529188890 108073
##
## Step: AIC=108066.9
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 1527145856 108067
## + MACHINE 1 13406 1527132449 108069
## - DATE 1 722823 1527868679 108069
## - EXPERIMENTER 4 2120600 1529266456 108071
## [1] "NK.CD56HI panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-73642.28
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 0.00005771 2.4208 -73644
## - DATE 1 0.00015548 2.4209 -73644
## - EXPERIMENTER 4 0.00179107 2.4225 -73644
## <none> 2.4207 -73642
##
## Step: AIC=-73644.07
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.00011820 2.4209 -73646
## - EXPERIMENTER 4 0.00184273 2.4226 -73645
## <none> 2.4208 -73644
## + MACHINE 1 0.00005771 2.4207 -73642
##
## Step: AIC=-73645.63
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 0.00210588 2.4230 -73646
## <none> 2.4209 -73646
## + DATE 1 0.00011820 2.4208 -73644
## + MACHINE 1 0.00002043 2.4209 -73644
##
## Step: AIC=-73645.83
## TARGET ~ 1
##
## Df Sum of Sq RSS AIC
## <none> 2.4230 -73646
## + EXPERIMENTER 4 0.00210588 2.4209 -73646
## + DATE 1 0.00038135 2.4226 -73645
## + MACHINE 1 0.00002171 2.4230 -73644
## Start: AIC=-7777.2
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.00002768 0.10924 -7781.0
## <none> 0.10922 -7777.2
## - DATE 1 0.00036147 0.10958 -7776.3
##
## Step: AIC=-7780.98
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 0.10924 -7781.0
## - DATE 1 0.00052456 0.10977 -7778.8
## + EXPERIMENTER 2 0.00002768 0.10922 -7777.2
## Start: AIC=-6328.21
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.00063147 0.58154 -6329.3
## <none> 0.58091 -6328.2
## - EXPERIMENTER 2 0.00284821 0.58375 -6328.0
##
## Step: AIC=-6329.27
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 0.58154 -6329.3
## + DATE 1 0.0006315 0.58091 -6328.2
## - EXPERIMENTER 2 0.0051394 0.58668 -6325.6
## [1] "NK.CD56HI panel2 CBCS"
## [1] "NK.CD56LO panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=179937.1
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 4.6035e+12 179937
## - MACHINE 1 3.7464e+09 4.6072e+12 179942
## - DATE 1 5.8636e+09 4.6093e+12 179947
## - EXPERIMENTER 4 1.2993e+10 4.6165e+12 179954
## [1] "NK.CD56LO panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-44773.55
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 60.618 -44774
## - DATE 1 0.014310 60.632 -44773
## - MACHINE 1 0.022331 60.640 -44772
## - EXPERIMENTER 4 0.202735 60.821 -44752
## Start: AIC=-4437.85
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.003005 5.1437 -4439.3
## <none> 5.1407 -4437.9
## - EXPERIMENTER 2 0.048299 5.1890 -4433.7
##
## Step: AIC=-4439.35
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 5.1437 -4439.3
## + DATE 1 0.003005 5.1407 -4437.9
## - EXPERIMENTER 2 0.058087 5.2017 -4433.6
## Start: AIC=-4167.93
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.0001115 7.0183 -4169.9
## - EXPERIMENTER 2 0.0269510 7.0452 -4168.6
## <none> 7.0182 -4167.9
##
## Step: AIC=-4169.92
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.0284816 7.0468 -4170.4
## <none> 7.0183 -4169.9
## + DATE 1 0.0001115 7.0182 -4167.9
##
## Step: AIC=-4170.41
## TARGET ~ 1
##
## Df Sum of Sq RSS AIC
## <none> 7.0468 -4170.4
## + EXPERIMENTER 2 0.0284816 7.0183 -4169.9
## + DATE 1 0.0016421 7.0452 -4168.6
## [1] "NK.CD56LO panel2 CBCS"
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=130466.4
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 9877 1.8627e+10 130464
## <none> 1.8627e+10 130466
## - MACHINE 1 6367549 1.8633e+10 130467
## - EXPERIMENTER 4 69507394 1.8696e+10 130492
##
## Step: AIC=130464.4
## TARGET ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 1.8627e+10 130464
## - MACHINE 1 6689067 1.8633e+10 130466
## + DATE 1 9877 1.8627e+10 130466
## - EXPERIMENTER 4 82072935 1.8709e+10 130496
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-38288.32
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 124.75 -38288
## - MACHINE 1 0.07611 124.83 -38285
## - DATE 1 0.08200 124.83 -38284
## - EXPERIMENTER 4 0.40266 125.15 -38267
## Start: AIC=-3617.71
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.023285 13.262 -3620.2
## <none> 13.239 -3617.7
## - DATE 1 0.058372 13.297 -3615.9
##
## Step: AIC=-3620.19
## TARGET ~ DATE
##
## Df Sum of Sq RSS AIC
## <none> 13.262 -3620.2
## - DATE 1 0.039715 13.302 -3619.6
## + EXPERIMENTER 2 0.023285 13.239 -3617.7
## Start: AIC=-4350.74
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.000043 5.6841 -4352.7
## <none> 5.6840 -4350.7
## - EXPERIMENTER 2 0.109176 5.7932 -4338.2
##
## Step: AIC=-4352.73
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 5.6841 -4352.7
## + DATE 1 0.000043 5.6840 -4350.7
## - EXPERIMENTER 2 0.124523 5.8086 -4337.9
## [1] "Plasmacytoid.DC.(CD11c-.CD123+) panel2 CBCS"
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=177896.7
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 1.6375e+07 3.6747e+12 177895
## <none> 3.6747e+12 177897
## - MACHINE 1 5.1785e+09 3.6799e+12 177907
## - EXPERIMENTER 4 7.1196e+10 3.7459e+12 178061
##
## Step: AIC=177894.8
## TARGET ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 3.6747e+12 177895
## + DATE 1 1.6375e+07 3.6747e+12 177897
## - MACHINE 1 5.3912e+09 3.6801e+12 177906
## - EXPERIMENTER 4 8.9347e+10 3.7641e+12 178102
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=12960.57
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 4 13.5775 38020 12956
## - DATE 1 0.0130 38006 12959
## - MACHINE 1 3.7722 38010 12960
## <none> 38006 12961
##
## Step: AIC=12955.77
## TARGET ~ DATE + MACHINE
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.0253 38020 12954
## - MACHINE 1 2.9341 38023 12954
## <none> 38020 12956
## + EXPERIMENTER 4 13.5775 38006 12961
##
## Step: AIC=12953.78
## TARGET ~ MACHINE
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 3.3410 38023 12953
## <none> 38020 12954
## + DATE 1 0.0253 38020 12956
## + EXPERIMENTER 4 13.5898 38006 12959
##
## Step: AIC=12952.56
## TARGET ~ 1
##
## Df Sum of Sq RSS AIC
## <none> 38023 12953
## + MACHINE 1 3.3410 38020 12954
## + DATE 1 0.4322 38023 12954
## + EXPERIMENTER 4 13.0090 38010 12958
## Start: AIC=-3168.56
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.00619 22.230 -3170.3
## - EXPERIMENTER 2 0.08147 22.306 -3169.4
## <none> 22.224 -3168.6
##
## Step: AIC=-3170.32
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - EXPERIMENTER 2 0.077445 22.308 -3171.3
## <none> 22.230 -3170.3
## + DATE 1 0.006190 22.224 -3168.6
##
## Step: AIC=-3171.3
## TARGET ~ 1
##
## Df Sum of Sq RSS AIC
## <none> 22.308 -3171.3
## + EXPERIMENTER 2 0.077445 22.230 -3170.3
## + DATE 1 0.002164 22.306 -3169.4
## Start: AIC=-4658.31
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 0.00307 3.9896 -4659.6
## <none> 3.9865 -4658.3
## - EXPERIMENTER 2 0.28753 4.2740 -4601.9
##
## Step: AIC=-4659.64
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 3.9896 -4659.6
## + DATE 1 0.00307 3.9865 -4658.3
## - EXPERIMENTER 2 0.29808 4.2876 -4601.2
## [1] "Classical.monocytes.(CD16-.CD14+) panel2 CBCS"
## [1] "DC.(HLA-DR+) panel2 COUNTS"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Warning: NAs introduced by coercion
## Start: AIC=153074.9
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - DATE 1 7009779 2.3091e+11 153073
## - MACHINE 1 25938982 2.3093e+11 153074
## <none> 2.3091e+11 153075
## - EXPERIMENTER 4 5787683692 2.3669e+11 153289
##
## Step: AIC=153073.1
## TARGET ~ MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## - MACHINE 1 20816238 2.3094e+11 153072
## <none> 2.3091e+11 153073
## + DATE 1 7009779 2.3091e+11 153075
## - EXPERIMENTER 4 7230002864 2.3814e+11 153342
##
## Step: AIC=153071.9
## TARGET ~ EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 2.3094e+11 153072
## + MACHINE 1 20816238 2.3091e+11 153073
## + DATE 1 1887034 2.3093e+11 153074
## - EXPERIMENTER 4 7209657112 2.3814e+11 153340
## [1] "DC.(HLA-DR+) panel2 FREQ"
##
## 0
## 867
## Warning in cor.test.default(as.numeric(merge[, c(ocCol)]),
## as.numeric(merge[, : Cannot compute exact p-value with ties
## Start: AIC=-71107.27
## TARGET ~ DATE + MACHINE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 3.2312 -71107
## - MACHINE 1 0.001012 3.2322 -71106
## - DATE 1 0.001258 3.2324 -71106
## - EXPERIMENTER 4 0.050047 3.2812 -70977
## Start: AIC=-7232.02
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 0.20482 -7232.0
## - DATE 1 0.0033047 0.20813 -7220.1
## - EXPERIMENTER 2 0.0122255 0.21705 -7185.8
## Start: AIC=-7514.24
## TARGET ~ DATE + EXPERIMENTER
##
## Df Sum of Sq RSS AIC
## <none> 0.14791 -7514.2
## - DATE 1 0.0025357 0.15045 -7501.5
## - EXPERIMENTER 2 0.0119240 0.15984 -7451.0
## [1] "DC.(HLA-DR+) panel2 CBCS"
# results=results[-order(results$METRIC),]
results$COMP_LOOK =gsub(".", " ",results$COMP_LOOK,fixed = TRUE)
write.table(
results,
sep = "\t",
quote = FALSE,
file = paste0(dir,"testResults.txt"),
row.names = FALSE
)